One of the greatest challenges in biology is to determine the complete molecular composition of cells and their sub-compartments. Currently, the state-of-the-art for tackling this problem is to purify compartments or macromolecular complexes of interest, and determine their components (e.g., proteins) by mass spectrometry. Such conventional proteomics methods are not capable to provide a comprehensive assessment of the proteome of living cells or of substructures within living cells, such as organelles, or macromolecular complexes. While some conventional approaches to proteomic analysis, e.g., based on mass spectrometry (MS) allow for the unbiased identification of nearly all proteins in a complex sample, they are limited by the fact that they cannot be performed on living cells. Sample preparation for current proteomics assays requires lysis of biological material, and, therefore, spatial and dynamic information cannot be analyzed.
Currently used approaches to solve this problem rely on the purification of spatially-defined components of interest from cells after lysis. For example, mitochondria, ER, and other organelles are purified by repeated centrifugation and fractionation steps, while macromolecular complexes are purified using antibodies or affinity tags. However, these purifications have drawbacks. For example, current purification methods typically lead to numerous false positives and false negatives, and many subcellular structures of live cells are not amenable to purification. For example, in neurons, it would be transformative to know the complete molecular composition of the synaptic cleft, but this structure cannot be purified. Likewise, although the mitochondrial proteome has been characterized, it would be illuminating to separately map the proteomes of the mitochondrial inter-membrane space, outer mitochondrial membrane, and contact sites between mitochondria and the endoplasmic reticulum. However, these proteomes are currently unknown because they cannot be purified.